Archive for the ‘ai-one Consulting Partners’ Category

Applying ai-one’s technology to the world’s information problems is an exciting part of our job. There isn’t a week that goes by without a customer in a new domain experiencing the pain caused by big data and lousy language tools. While we love the breadth of this challenge, each of us has our favorite problem we would love to focus on to change the world.

For Olin Hyde, our former VP Business Development, it has always been medicine. He has the intellectual curiosity and bandwidth to understand medicine and its intersection with information technology, and has lobbied for us to focus solely on this market. Within our partner model, this passion was focused on trying to find and develop an OEM Partner to work with. Since he couldn’t find one, on August 1st he did what any good entrepreneur would do when he sees a big opportunity, he founded his own company. His mission for Englue Inc. is to become the ai-one OEM Partner that will change medicine’s approach to research.

Are we bummed he left? Sure we are. But he hasn’t left the family and as a partner applying our unique form of biologically inspired intelligence to medical research, we are confident Olin will create a big success story for both of us. This form of intelligence will spawn a huge number of new applications over the next decade. Olin has been part of a team that has ten years’ experience applying this new form of computing to real application problems giving him a huge competitive advantage.

Building off our new Nathan API and the platform and tools ai-one calls the Analyst Toolbox, Englue will be launching a series of products for the medical researcher that will enable them to fully leverage the vast amount of publications and clinical studies from around the globe. We look forward to working with Olin and the Englue team and wish him the best of success.

On November 29, 2011, our consulting partner Ariston Consulting submitted a proposal to the US Air Force to develop a new form of defense for cyber assets using machine learning for cyber awareness and resilience. This proposal was partially developed by ai-one in an effort to bring the most advanced machine learning technologies to the Air Force at the lowest possible cost.

Our proposal (below) was in response to BAA Number AFRL-PK-11-0001 as a Rapid Innovation Funding program. Our proposal met all four operational criteria yet was rejected on January 6, 2012 due to our lack of prior history with the US Air Force. The AF simply preferred to do business with a company that they knew rather than a new vendor.

However, on December 20, 2011 the Air Force released a request to build a system very similar to what we proposed to build below under the contract BAA-RIK-12-03. Both projects were issued by the Department of the Air Force, Air Force Materiel Command, AFRL – Rome Research Site, AFRL/Information Directorate, 26 Electronic Parkway, Rome, NY, 13441-4514.

We are not accusing the Air Force of any wrong doing nor is there any evidence that they copied and pasted our ideas into another BAA. Quite to the contrary, the Air Force is a big place and we are not the only people thinking of ways for networks to defend themselves using autonomic machine learning technologies. However, we feel that our technology can be deployed at very minimal cost compared to the budget provided in the BAA issued a month after we proposed a smaller, more rapid solution.

We think it is valuable to share this information with the public for several reasons:

To publish our findings in a public forum to prevent any other party from obtaining a patent for cyber security applications or network defense applications using the approach described herein.

To encourage major defense contractors to contact Ariston Consulting and to use ai-one’s biologically inspired intelligence in cyber security applications.

To encourage the Air Force to consider reducing the budget allocated for BAA-RIK-12-03 by 90%. There is simply no business reason to spend 10-times what we proposed.

Ariston Consulting LLC proposes to develop a Self-Aware, Self-Defending Adaptive Network Appliance Software (SASDANAS) system that acts as an intelligent agent to monitor network activity, content and behavior to augment the capacity of human analysts to identify and counteract all forms of cyber threats.

Ariston Consulting is a Service-Disabled Veteran-Owned Small Business (SDVOSB) based in Sierra Vista, AZ, provides advanced technology testing and engineering solutions. Expertise and experience in providing non-personal scientific and engineering services to test Command, Control, Communications, Computers, Intelligence, Surveillance and Reconnaissance (C4ISR) systems in support of the US Air Force (USAF), US Army, and DISA.

SASDANAS is an intelligent agent that learns and understands the threat level posed by every byte-pattern across a network. The software system uses a new form of machine learning to monitor every detail of a network to identify and isolate cyber security threats – including malware, application high-jacking, sabotage and illicit access, hacking and unauthorized use. It enables the Air Force to make all cyber assets self-aware, self-protecting and adaptive to any external or internal threat. The approach eliminates the opportunity for zero-day attacks because it detects all anomalous packet behavior and content. Furthermore, SASDANAS provides the Air Force with a first-mover advantage as the system learns through use and thus becomes more intelligent over time.

SASDANAS is a 64-bit multithread, massively parallel application that is deployable through a REpresentational state transfer (REST) architecture. Each instance of SASDANAS may be deployed in series and/or in parallel. This architecture provides the USAF the greatest degree of flexibility when deploying into field operations. This approach enables the USAF to use SANDANAS in either: a) moving-windows approach to read every packet as it flows across the network; or, b) identifying threats by capturing an image of the topology of network at byte- or packet-level of detail to understand the behavior and content of network. Each instance of SASDANAS will have the capacity to understand up to 18 exabytes of data at a time. Speed of SASDANAS is dependent on available memory and processing capacity. When deployed in parallel, SASDANAS has the theoretical capacity to monitor the activity of the entire Internet.

Unlike current approaches to cyber security, SASDANA uses a new technology called a HoloSemantic DataSpace (HSDS) to detect, classify and store every byte pattern. The HSDS is thus able to recognize every packet’s behavior and content to determine if the byte-pattern conforms to expectations or is anomalous and therefore subject to further scrutiny to determine if it is a threat. The HSDS is an adaptive, associative network that detects the relationship of every byte that is fed into the system. Thus, the HSDS is capable of identifying both known threat patterns while concurrently identifying and isolating anomalous patterns that may signify a zero-day attack or non-compliant use of the network (e.g., sabotage).

The HSDS is a newly discovered form of neuronal network that mimics the neurophysiology of the neocortex. It is commercially trademarked as a “biologically inspired intelligence” and operates similar to a human brain. It learns autonomically by detecting byte-patterns at the moment of stimulation. The HSDS stores each unique byte pattern only once regardless of how many times it encounters that specific pattern. It registers and adjusts the semiotic value for each byte pattern each time it is stimulated – adjusting the size of the net automatically. It determines the semiotic value for each byte pattern with the following dimensions, each of which may have many values: time of stimulation, place of stimulation, syntax of surrounding byte patterns, and packet payload and addressing. Thus, the HSDS creates an n-dimensional representation of the semiotic value of every byte-pattern; thereby capturing every detail within the complexity of data.

The HSDS technology is commercially available from ai-one inc. since June 2011. It is currently in use at Orange (France Telecom) and more than 40 additional installation sites around the world. The commercial version of the HSDS is offered in three versions: Topic-Mapper to analyze human languages, graphalizer to analyze sensor data, and Ultra-Match to analyze visual images. The technology has been used by The Federal Criminal Police Office of Germany (Bundeskriminalamt or BKA) to build a crime scene analysis tool for the Swiss Federal Department of Justice and Police (Eidgenössische Justiz- und Polizeidepartement or EJPD). The commercial versions of HSDS have a technology readiness level (TRL) of 9. The TRL for the proposed customization of current HSDS COTS technology is 7. Ariston Consulting will license ai-one’s technology to create a new software application to meet the unique needs of protecting USAF cyber assets. The HSDS differs from current forms of neural networks, machine learning and artificial intelligence technologies in the following ways:

Transparency – HSDS generates a lightweight ontology (LWO) that adjusts dynamically with each passing byte (and/or packet). The LWO describes the relationship of every byte within the network. The LWO is machine generated, machine curated and accessible by humans.

Benefit: Humans can see how SASDANAS interprets the value and threat level of every packet.

Autonomic: HSDS learns without any human intervention. It does not require any prior conditions or neighborhood functions. Rather, it automatically generates computational and data cells within the network as needed immediately upon network stimulation – just like the human brain.

Benefit: SASDANAS is objective and subject to cognitive biases that may distort threat detection.

Speed, Accuracy, Sensitivity: HSDS captures every detail regardless of the degree of complexity. In incremental learning situations, the proposed 64-bit architecture is expected to be at least 105 faster than latent Dirichlet allocation (LDA) or vectoring approaches such as COStf-idf.

Benefit: SASDANAS is very fast and accurate – even by neural net standards.

Trainability: The system can be trained and untrained by humans. It is aware of which patterns are learned through training and which patterns have been taught from humans.

Benefit: SASDANAS eliminates the risk of overtraining. It is flexible.

Compatible with Existing Technologies: The system is deployable using industry standard approaches as a cloud-based application.

Benefit: SASDANAS reduces the cost of maintaining and protecting cyber assets while extending their functionality.

Ariston Consulting proposes to build SASDANAS as a software proof-of-concept for further development as a hardware solution called Self-Aware, Self-Defending Adaptive Network Appliance Chipsets (SASDANACS). Based on preliminary tests of the core commercial technology, Ariston estimates that the hardware version will operate at least 10,000 times faster than the software version. This speed, combined with an estimated capacity of 18 exabytes per instance, enables the hardware version to monitor and protect cyber assets at wire-speed and at Internet scale.

SASDANA is deployable at any layer with network (from switch layers 1 through 7) and is compatible with known specifications for Wireless Network After Next (WNAN) as described in unclassified DARPA and AFRL reports. Its architecture provides the AF with a wide range of deployment options.

Approach:

Ariston Consulting LLC will adapt commercial-off-the-shelf (COTS) HSDS software from ai-one inc. to build SASDANA. Ariston Consulting has secured rights to license and modify technologies owned by ai-one inc.for the purpose of creating custom applications for agencies of the United States Government, including the Department of Defense.

iii) Ability to detect anomalous behavior of a packet within a network.

e) Facilities/Equipment:

i) All development will be completed at an Ariston consulting controlled Top Secret (TS) facility.

f) Risk:

i) Technical risk of SASDANAS is minimal as the technology currently is available for commercial use by ai-one inc. Ariston Consulting will mitigate risk by employing ai-one engineers to train Ariston staff, transfer knowledge and provide guidance based on commercial experience.

g) Proposed Transition Plan:

i) Technical data: Unlimited rights granted to USAF.

ii) Non-commercial software (NCS): Unlimited rights granted for each additional instance of SASDANAS software shall be sold to the US Government.

iii) NCS Documentation: Unlimited rights granted to USAF.

iv) Commercial computer software rights: Not applicable. SASDANAS will be a modified version of ai-one technology that will not be commercially available.

v) There are no restrictions on the use of a licensed instance of SASDANAS for use within the United States Air Force. The Air Force may deploy SASDANAS at its own discretion, in any manner it so chooses.

vi) SASDANA’s application program interface (API) may be accessed by any entity authorized by the USAF.

“This technology enables us to do far better testing in less time on far less money.” said Woody Woodruff, Founder and CEO of Ariston. “We can now automate the most burdensome tasks for human analysts.”The partnership provides Ariston with a first mover advantage in building custom solutions for the DoD using a new generation of artificial intelligence tools that were released to the market in June 2011. These tools enable software developers to build machine learning into applications so computers can recognize patterns and associations much like a human.

The impact is potentially huge. More than ten percent of the DoD budget is spent on research development test and evaluation according to a report to a May 17, 2011 report to the House Committee on Armed Services.

ai-one’s technology differs from other forms of artificial intelligence because it learns without any human intervention. It detects the inherent structure of data in very complex environments so computers can recognize patterns and associations – even for the faintest signals. It automatically builds a database (called a lightweight ontology that shows humans how any piece of data relates to another. The technology works with any digital file – including text, images and radio signals.

Ariston plans to start using ai-one’s Topic-Mapper product for text analytics to evaluate messaging systems for the US Army Electronic Proving Grounds. Olin Hyde, VP of Business Development for ai-one explained that “It is language agnostic. So it is ideal for finding patterns where people don’t use conventional grammar or words. For example, it can find the sentiments in Twitter feeds with only a few commands.”

Future plans include using it to analyze threat patterns in cyber security, cataloging radio signals, network monitoring and management and other trial analysis programs. “The core technology plays broadly in the C5ISR space,” said Woodruff, “the key will be finding areas where we can prove immediate returns on investment. The cost is low – so we expect it will be a question of just picking the right test environments to focus our efforts.”

About Ariston Consulting LLC., is a Service-Disabled Veteran-Owned Small Business (SDVOSB) based in Sierra Vista, AZ, providing the best testing and engineering solutions designed for today’s defense industry challenges. Ariston’s diversified experts provide solutions for test methodology and design, operational, developmental and interoperability test services, analytical and data services. Current clients include: Joint Interoperability Test Command (JITC) and the U.S. Army Test and Evaluation Command Electronic Proving Grounds (EPG) at Fort Huachuca, AZ and the U.S. Air Force Joint Test and Evaluation Joint UAS Digital Information Exchange (JUDIE) effort at Nellis AFB, NV. In addition, Ariston is a specialist in providing Department of Homeland Security Independent Test and Evaluation services with staff experience as the Independent Tester of Secure Border Initiative Network and Project 28.

Press Release

For Immediate Release: August 4, 2011

San Diego artificial intelligence startup acquired by leading provider of machine learning SDKs as market for advanced applications gets hot.

San Diego CA – ai-one announced today that it acquired Auto-Semantics, a local start-up providing artificial intelligence services to corporate IT departments. The acquisition is the latest in a series of joint-ventures and acquisitions by ai-one that consolidates its leadership position within the emerging market for machine learning technologies.

In less than one year from its founding, Auto-Semantics built a solid pipeline of commercial accounts to apply computational semantics to solve “big data” and marketing problems – such as modeling consumer and investor behaviors. Computational semantics is a set of technologies that enables machines to understand human language. Olin Hyde started the company to build a “smart, personalized mobile GroupOn” application to deliver coupons but was unable attract capital for that concept. “Not getting funding was a blessing – it forced me to pivot from building speculative products into providing professional services. We solved corporate IT problems using machine learning technologies. That led me to ai-one – they had the only SDK to build semantic applications.” said Hyde.

ai-one provides programming tools that enable software developers to build machine learning into applications, websites and mobile phones. The company was founded in Zurich, Switzerland in 2003 and reincorporated as a US corporation in 2009 in anticipation of going public in 2012. Unlike most technology startups, ai-one spent more than eight years developing the core technology using funding from private investors from Europe.

The technology is distributed through consulting partnerships that use it to build custom solutions for corporations and government agencies. “A lot of people ask us about who uses our technology,” said ai-one’s President Tom Marsh, “and the fact is our customers are working on very proprietary, often secret, solutions. There are many new applications in the pipeline coming from our partners that will hit the market in late 2011 and early 2012. It’s an exciting time for us.”

Hyde met Marsh at a local MeetUp group and later, ai-one founders Walt Diggelmann and Manfred Hoffleisch at the SDSIC SuperMath conference. Auto-Semantics signed up as an ai-one Consulting Partner on the first day the program became available. “It was clear from the beginning that Olin had the pulse on what corporate CIOs were thinking,” said Marsh, “He gets how to communicate the value of our big idea: Machines can learn just like we do, and you don’t have to be IBM or Google to play in this space. Olin fits our entrepreneurial culture with international business experience.” The stock transaction ties Hyde to ai-one where he will serve as Vice President of Business Development.

ai-one also acquired Berlin-based PPM Data Management GmbH last year and formed two joint-ventures earlier this year that embed ai-one’s advanced pattern recognition technology in commercial services: ai-ibiomics gmbh provides personalized medicine using genetic sequencing and Forensity AG sells shoeprint recognition software to law enforcement agencies and crime laboratories.

Press Release

Brazilian Arquiware signs deal to use new machine learning SDK to enhance sentiment analysis of social media networks.

La Jolla CA | São Paulo – Marketing consumer products in Brazil is about to get a lot easier thanks to a small, innovative software company. Arquiware is combining artificial intelligence with natural language processing to enable companies to analyze feelings and opinions social media networks. They are among the first in the world to apply techniques to create tools that enable companies to understand the sentiments of customers.

“Many multi-nationals come to Brazil then realize that it takes more than understanding Portuguese to understand how a brand interacts with consumers.” said Luis Lima, President of Arquiware, “In fact, the diversity of Brazil makes it almost impossible to understand our market unless you use sophisticated tools to extract the true meaning of what people are saying about you.”

Arquiware will add ai-one’s Topic-Mapper SDK to build artificial intelligence into two existing products. SentimentWare and TopicExtractWare analyze text data from social media networks and news feeds. The new capability gives Arquiware clients the ability to understand how any given news event will impact the perception of a brand.

ai-one’s technology is used by telecom companies, security and law enforcement agencies to enable computers to read text in a similar manner to humans. “We are thrilled that Arquiware will apply our technology to social media sentiment analysis. They are ahead of the efforts I have seen in Silicon Valley,” commented Olin Hyde, VP of Business Development for ai-one.

About Arquiware DSC (Brazil), Arquiware is one of Brazil’s leading software companies specializing in application development using natural language processing (NLP) and text mining. Arquiware builds custom applications for numerous enterprise clients and sells commercial off-the-shelf products for sentiment analysis and text extraction. SentimentWare provides sentiment analysis of social networks using the Radian6 API. TopicExtractWare is a SaaS that summarizes the meaning of any corpus of text by distilling information into tag clouds. Visit Arquiware’s free sentiment analysis of Twitter feeds to determine the best samba school in Carnival.

Press Release

KAPS Group plans to use new machine learning SDK to build advanced knowledge management applications for enterprise clients.

La Jolla CA | Oakland CA – KAPS Group announced today they would start using ai-one’s machine learning technologies to build custom applications for large corporations and government agencies. KAPS specializes in designing and developing systems that add semantic intelligence to unstructured content. These systems range from enterprise search to sentiment analysis-based customer intelligence to knowledge management systems that enable organizations to capture and use the information that employees learn through years of on-the-job experience. These systems are becoming increasingly important as companies struggle to retain expertise as expert employees retire or leave the company.

Semantic Structure Key to Knowledge Management

Tom Reamy, Chief Knowledge Architect at KAPS, sees the market continuing to grow. “There is a growing realization that adding semantic structure is the only way to make sense of all the extremely valuable, unrealized content that resides in today’s organizations. This is true for the information and knowledge in documents and in the expertise of employees. And capturing, organizing, and structuring that information is what will drive companies to be more innovative, responsive, and profitable.”

The Value of Machine Learning

KAPS partnered with ai-one inc to gain access to software development kits (SDK) that enable programmers to build machine learning into other applications. These SDKs make it possible for computers to automatically read and learn the meaning of vast amounts of unstructured data by how words are associated with each other. For example, a system might read millions of emails on a drug discovery process to learn that two chemicals could achieve the same result – even though one of the chemicals was ignored by a research team.

“It is an honor to have KAPS as a partner,” said Olin Hyde, ai-one’s VP of Business Development, “they have a fantastic reputation for building state-of-the-art systems.” Previous KAPS clients include the FDA, GAO, Genentech, Visa and Amdocs.

About KAPS Group LLC

Led by Chief Knowledge Architect, Tom Reamy, KAPS is a group of knowledge architecture consultants with a wide range of skills and experience. The firm’s services include: text analytics categorization and entity extraction catalogs, taxonomy creation, design and implementation of metadata and controlled vocabularies, implementation of search, content management, and portals, and strategic consulting. Based in Oakland California, KAPS Group’s services are grounded in the creation and maintenance of the intellectual infrastructure of an organization. This intellectual infrastructure consists of a wide variety of content and knowledge structures from metadata and taxonomies to linked data and ontologies, information technologies, the information processes embedded within business procedures, and the information/knowledge needs and behaviors of individual people and social communities.

Press Release

DotNet Tech plans to use new machine learning SDK to bring advanced analysis of unstructured data into Crystal Reports services.

La JollaCA| Zurich| Berlin– Crystal Reports is about to get a lot smarter. Brian Bischof, widely regarded as the leading authority on Crystal Reports, just signed a deal to become an IT Services Consulting Partner with ai-one inc. The deal will give Bischof’s company, DotNet Tech, access to ai-one’s Topic-Mapper SDK to develop custom reporting tools that use artificial intelligence to report on unstructured data.

Crystal Reports, owned by SAP, is one of the most popular tools to create reports using information stored in databases. One of the biggest problems facing IT departments is reporting on data that is not easily categorized – such as feeds of text from the internet and social media.

ai-one’s Topic-Mapper enables Crystal Reports to read and ingest text in much the same was a human. This is the first deal that enables a consulting firm to build artificial intelligence into a common reporting tool.

“Gone are the days of trying to work around unstructured data,” said Bischof, “Now we can use ai-one’s Topic-Mapper to learn the inherent structure within any corpus. Now we can process and include everything from Twitter feeds and Facebook postings into Crystal Reports using Microsoft’s Visual Studio.

Olin Hyde, VP of Business Development added “I’ve known Brian for a long time. He is a fantastic, visionary developer. I can’t wait to see what he does with Topic-Mapper combined with Crystal Reports and Visual Studio.”

About DotNet Tech, Inc., Led by founder, Brian Bischof, CPA is a systems consulting firm specializing in the development of advanced web-based applications using Microsoft’s .NET suite of development tools. Bischof is also the best-selling author of Crystal Reports books. Clients include University of California San Diego and more than 10,000 subscribers to www.CrystalReportsBook.com.

Press Release

It is no secret that for many years global banks have used artificial intelligence to make better trades. Now that technology might be coming to your local independent investment advisory service.

Caapi Technologies just announced that it signed a deal to use artificial intelligence technology to build custom trading systems for small to mid-size investment firms. Caapi will build applications with software development kits (SDKs) from ai-one that enable computers to understand human language to find undervalued stocks, bonds and derivatives.

The partnership makes Caapi one of the first consulting firms to use ai-one’s machine learning technology to build trading algorithms and platforms for traders, banks and hedge funds.

Building custom trading algorithms is a huge industry propelled by the success of high-frequency trading across global markets. Originally, these algorithms were designed to find and exploit pricing differences between stocks, commodities and derivatives. Now trading algorithms are so widespread and so sophisticated that they have completely reshaped markets to the point where pricing is often driven more by speculation than it is by the underlying value of the asset class.

The challenge now is to find underpriced opportunities that generate returns based on actual performance rather than market volatility. This requires that investors sort through vast amounts of unstructured data to find undervalued assets before they are identified by the rest of the market. Often this means reading text that can’t be processed by search engines like Google. Traditional algorithmic approaches, such as Google’s, fail as they only know what they are programmed to know or programmed to find. They miss finding unexpected results that don’t fit into an equation.

ai-one’s technology is described as “biologically inspired intelligence.” It is modeled after the human brain and does not depend on algorithms. Rather, it automatically sees the inherent patterns within data and forms associations between each data element. This enables machines to learn without any human intervention. More importantly, it enables people to ask the questions they wouldn’t normally know to ask.

The CEO of Caapi, Mr. Moris Oz, sees machine learning as the key to discovering hidden investment opportunities. “a-one’s technology enables us to build semantic associative search engines for our clients that understand how the price of any given investment is related to the unstructured data found on the internet.”

Caapi’s approach is to combine proven techniques using sophisticated algorithms with machine learning that understands words. “Language is not math,” adds Olin Hyde, VP of Business Development at ai-one. “Algorithms are fantastic at processing structured data. But human behaviors and communications are inherently unstructured and complex. We learn through words not equations. So why not enable computers to do the same?”

According to Moris Oz, CEO of Caapi, “ai-one’s SDK for machine learning could be the answer for understanding and correlating soft data driving price moves in the markets. I’m looking forward to applying this to new applications.” The market will soon tell if it works or not.